{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import datetime\n",
    "from influxdb import InfluxDBClient\n",
    "import talib as  ta\n",
    "import seaborn as sns\n",
    "import warnings\n",
    "from matplotlib import pyplot as plt\n",
    "warnings.filterwarnings('ignore')\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from statsmodels.tsa.arima_model import ARMA\n",
    "import warnings\n",
    "from itertools import product\n",
    "from datetime import datetime, timedelta\n",
    "import calendar\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "sqlday = \"select * from KlineDay where symbol='HSI' and  time > '2010-01-01 00:00:00'\"\n",
    "client = InfluxDBClient('192.168.3.108',8086)\n",
    "rsday = client.query(sqlday, database='KlineIndex')\n",
    "df = pd.DataFrame(rsday.get_points())\n",
    "\n",
    "df.time = df.time.apply(lambda x: x[0:10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>21823.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-01-05</td>\n",
       "      <td>22279.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-06</td>\n",
       "      <td>22416.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-07</td>\n",
       "      <td>22269.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-08</td>\n",
       "      <td>22296.75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         time     close\n",
       "0  2010-01-04  21823.28\n",
       "1  2010-01-05  22279.58\n",
       "2  2010-01-06  22416.67\n",
       "3  2010-01-07  22269.45\n",
       "4  2010-01-08  22296.75"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "usecols=['time','close']\n",
    "df_train = df[usecols].copy()\n",
    "df_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>21823.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>22279.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-06</th>\n",
       "      <td>22416.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-07</th>\n",
       "      <td>22269.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-08</th>\n",
       "      <td>22296.75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               close\n",
       "time                \n",
       "2010-01-04  21823.28\n",
       "2010-01-05  22279.58\n",
       "2010-01-06  22416.67\n",
       "2010-01-07  22269.45\n",
       "2010-01-08  22296.75"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.time = pd.to_datetime(df_train.time)\n",
    "df_train= df_train.set_index('time')\n",
    "df_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-31</th>\n",
       "      <td>21408.796000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02-28</th>\n",
       "      <td>20244.108889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-03-31</th>\n",
       "      <td>21089.353043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-04-30</th>\n",
       "      <td>21623.799474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-05-31</th>\n",
       "      <td>19945.355500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-31</th>\n",
       "      <td>28537.134500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-30</th>\n",
       "      <td>28850.197143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-31</th>\n",
       "      <td>27256.134762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-31</th>\n",
       "      <td>25928.246364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-30</th>\n",
       "      <td>25220.901905</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>141 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   close\n",
       "time                    \n",
       "2010-01-31  21408.796000\n",
       "2010-02-28  20244.108889\n",
       "2010-03-31  21089.353043\n",
       "2010-04-30  21623.799474\n",
       "2010-05-31  19945.355500\n",
       "...                  ...\n",
       "2021-05-31  28537.134500\n",
       "2021-06-30  28850.197143\n",
       "2021-07-31  27256.134762\n",
       "2021-08-31  25928.246364\n",
       "2021-09-30  25220.901905\n",
       "\n",
       "[141 rows x 1 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_month = df_train.resample('M').mean()\n",
    "\n",
    "df_month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_Q = df_train.resample('Q').mean()\n",
    "df_A = df_train.resample('A').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2a7a2f52700>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[15, 7])\n",
    "plt.subplot(221)\n",
    "plt.plot(df_train.close, '-', label='按天')\n",
    "plt.legend()\n",
    "plt.subplot(222)\n",
    "plt.plot(df_month.close, '-', label='按月')\n",
    "plt.legend()\n",
    "plt.subplot(223)\n",
    "plt.plot(df_Q.close, '-', label='按季度')\n",
    "plt.legend()\n",
    "plt.subplot(224)\n",
    "plt.plot(df_A.close, '-', label='按年')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ps=range(0, 3)\n",
    "qs = range(0,3)\n",
    "\n",
    "parameters = product(ps, qs)\n",
    "paramters_list = list(parameters)\n",
    "\n",
    "results=[]\n",
    "best_aic = "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
